1. Field of the Invention
The present invention relates to road detection and object detection, and specifically, a method and an apparatus for detecting road partitions.
2. Description of the Related Art
The driving assistance system is becoming more popular. The LDW/RDW (Lane/Road detection warning) system, a subsystem of the driving assistance system, can avoid collisions and help to determine driving directions accurately. A road or lane detection is very important for the LDW/RDW system, because only by knowing road information can a further process such as warning be performed. In general, a road or a lane is detected by detecting road partitions.
The road partitions include road shoulders, white lines, fences and other objects by which a road area and lanes can be identified.
In general, there are two types of methods for detecting the road: a method by using features and a method by modeling.
In the method by using features, the road or lane of a road image is located by combining some road features, such as colored lines or lane edges.
In the method by modeling, a road model, such as a straight line or a parabola, is determined first, then the road is represented by some parameters.
Only a few specific features of the road partitions are considered in these two methods, therefore it is impossible to detect every feature of the road partitions flexibly. For example, the modeling method is applied to road shoulders, not to white lines or fences, and it is inefficient to construct a special model for each road partition.
In the cited reference (U.S. Pat. No. 7,346,190B2), a method for detecting a road is disclosed. In this method, three-dimensional coordinates are projected as two-dimensional coordinates along a direction across the road, histograms along the direction across the road are generated, and lane lines are determined according to the histograms. This method is invalid in cases where height of the road is different, like a sloping road.
Furthermore, most of road detections in prior art are based on a single color image or a polarizing image, therefore it is inefficient for the road detection in cases of a feeble image of a road edge or a complicated environment with a slanted road.